Earth Observation for the Implementation of Sustainable Development Goal 11 Indicators at Local Scale: Monitoring of the Migrant Population Distribution

The present study proposes a method based on the integration of EO and census data for updating the spatial distribution map of the migrant population regularly residing in an area very exposed to migration on the Southern Mediterranean coast, i.e. Bari (Italy) and its surrounding areas. The method implemented is a vector-based variant of the dasymetric mapping approach used by the Joint Research Center (JRC) within the Data for Integration initiative to disaggregate data from census areas into a uniform grid and it draws on updated census data (1st January 2019) concerning regular migrant population, an updated human settlements (built-up) map and information about their use. The mapping of the built-up areas results from either a data-driven or knowledge-driven automatic classification techniques of multi-temporal Sentinel-2 satellite images acquired during 2018 with 10 m spatial resolution. The spatial distribution (density) map of regular migrant population obtained along with other updated ancillary data were used, at local (intra-urban) scale, to provide Sustainable Development Goal (SDG) 11 indicators. These include the ratio of land consumption rate to regular migrant population growth rate (SDG 11.3.1) and the map of regular migrant population living in inadequate housing (SDG 11.1.1) as specific categories of SDG 11 for the epochs 2011 and 2018. At the local level, the regular migrant population density map and the SDG 11 indicator values were provided for each cell of a 100 m by 100 m output grid. In recent literature, not many authors have tried to implement SDG 11 indicators at intra-urban scale. The findings obtained in the study area indicate an increase of migrant population up to 44.5% in 2018 with respect to the previous estimate provided by JRC and based on 2011 census data. In addition, the results reveal the tendency by the communities to aggregate in specific neighborhoods located in central areas of the city characterized by urban decay and abandoned buildings. The products obtained through the dasymetric method applied could be useful to support urban planners and decision makers not only in the management of increasing migration pressure but also for monitoring the progress in Agenda 2030 related to SDG 11 indicators at local level.